Table of contents

Motivated by recent advances in the physical and chemical basis of the Hofmeister effect, we measured the rate cell growth of S. aureus—a halophilic pathogenic bacterium—and of P. aeruginosa, an opportunistic pathogen, in the presence of different aqueous salt solutions at different concentrations (0.2, 0.6 and 0.9 M). Microorganism growth rates depend strongly on the kind of anion in the growth medium. In the case of S. aureus, chloride provides a favorable growth medium, while both kosmotropes (water structure makers) and chaotropes (water structure breakers) reduce the microorganism growth. In the case of P. aeruginosa, all ions affect adversely the bacterial survival. In both cases, the trends parallel the specific ion, or Hofmeister, sequences observed in a wide range of physico-chemical systems. The correspondence with specific ion effect obtained in other studies, on the activities of a DNA restriction enzyme, of horseradish peroxidase, and of Lipase A (Aspergillus niger) is particularly striking. This work provides compelling evidence for Hofmeister effects, physical chemistry in action, in these organisms.

A major goal of modern computational biology is to simulate the collective behaviour of large cell populations starting from the intricate web of molecular interactions occurring at the microscopic level. In this paper we describe a simplified model of cell metabolism, growth and proliferation, suitable for inclusion in a multicell simulator, now under development (Chignola R and Milotti E 2004 Physica A 338 261–6). Nutrients regulate the proliferation dynamics of tumour cells which adapt their behaviour to respond to changes in the biochemical composition of the environment. This modelling of nutrient metabolism and cell cycle at a mesoscopic scale level leads to a continuous flow of information between the two disparate spatiotemporal scales of molecular and cellular dynamics that can be simulated with modern computers and tested experimentally.

Many aquatic vertebrates can sense the weak electric fields generated by other animals and may also sense geoelectric or electromagnetic phenomena for use in orientation. All these sources generate stationary (dc) fields. In addition, fields from animals are modulated by respiration and other body movements. Since electroreceptors are insensitive to a pure dc field, it has been suggested that the ac modulation carries most of the relevant information for electrosensory animals. However, in a natural situation pure dc fields are rare since any relative movement between source and receiver will transform a dc field into a time varying signal. In this paper, we will describe the properties of such signals and how they are filtered at the first stage of electrosensory information processing in the brain. We will show that the signal perceived by an animal traversing a dc electric field contains all the information necessary to reconstruct the distance to the source and that the signal conditioning algorithms are perfectly adapted to preserve such information.

Riboswitches are RNA segments that serve as ligand-responsive genetic control elements. They modulate the expression of certain genes in response to changing concentrations of metabolites. In this paper, we study the dynamic behaviour of the B₁₂ riboswitch in E. coli—perhaps the most widely studied and best known of all riboswitches—through a mathematical model of its regulatory pathway. To carry this out, we simulate dynamic experiments in which the bacterial B₁₂ uptake capacity is measured after being depleted of this vitamin for a long time. The results of these simulations compare favourably with reported experimental data. The model also predicts that an overshoot of intracellular B₁₂ should be observed if the replenishment experiments were to be carried out for longer times. This behaviour is discussed in terms of a possible evolutionary advantage for E. coli, together with the fact that regulation at the transcriptional and translational levels is almost equivalent dynamically.

A prominent feature of gene transcription regulatory networks is the presence in large numbers of motifs, i.e., patterns of interconnection, in the networks. One such motif is the feed forward loop (FFL) consisting of three genes X, Y and Z. The protein product x of X controls the synthesis of protein product y of Y. Proteins x and y jointly regulate the synthesis of z proteins from the gene Z. The FFLs, depending on the nature of the regulating interactions, can be of eight different types which can again be classified into two categories: coherent and incoherent. In this paper, we study the noise characteristics of FFLs using the Langevin formalism and the Monte Carlo simulation technique based on the Gillespie algorithm. We calculate the variances around the mean protein levels in the steady states of the FFLs and find that, in the case of coherent FFLs, the most abundant FFL, namely, the type-1 coherent FFL, is the least noisy. This is shown to be true for all parameter values when the FFLs operate above their thresholds of activation/repression. In the case of incoherent FFLs, no such general conclusion can be shown. The results suggest possible relationships between noise, functionality and abundance.

Intracellular viral kinetics are of especial interest because the virion population inside an infected cell is well known to tend to grow exponentially and the corresponding kinetics may be unstable. To clarify the special features of such kinetics, we present Monte Carlo simulations taking into account the key steps of virion formation and competition of the host and viral mRNA for the host translation apparatus. Asymptotically, the model employed predicts either a stable steady state or 'ignition' with the unlimited viral growth. Under steady-state conditions, the mean square fluctuations of the viral genome and virion numbers are found to be appreciably larger than those expected on the basis of the Poissonian distribution. In the case of unstable kinetics, the simulations show the type of deviations from the corresponding mean-field results.

We investigate the reaction dynamics of diffusive molecules with immobile binding partners. The fixed reactants build clusters that are comprised of just a few tens of molecules, which leads to small cluster sizes. These molecules participate in the reaction only if they are activated. The dynamics of activation is mapped to a time-dependent size of an active region within the cluster. We focus on the deterministic description of the dynamics of a single cluster. The spatial setup accounts for one of the most important determinants of the dynamics of a cluster, i.e. diffusional transport of reaction partners towards or away from the active region of the cluster. We provide numerical and analytical evidence that diffusion influences decisively the dynamic regimes of the reactions. The application of our methods to intracellular Ca²⁺ dynamics shows that large local concentrations saturate the Ca²⁺ feedback to the channel state control. It eliminates oscillations depending on this feedback.

As our knowledge of biological processes advances, we are increasingly aware that cells actively position sub-cellular organelles and other constituents to control a wide range of biological processes. Many studies quantify the position and motion of, for example, fluorescently labeled proteins, protein aggregates, mRNA particles or virus particles. Both differential interference contrast (DIC) and fluorescence microscopy can visualize vesicles, nuclei or other small organelles moving inside cells. While such studies are increasingly important, there has been no complete analysis of the different tracking methods in use, especially from the practical point of view. Here we investigate these methods and clarify how well different algorithms work and also which factors play a role in assessing how accurately the position of an object can be determined. Specifically, we consider how ultimate performance is affected by magnification, by camera type (analog versus digital), by recording medium (VHS and SVHS tape versus direct tracking from camera), by image compression, by type of imaging used (fluorescence versus DIC images) and by a variety of sources of noise. We show that most methods are capable of nanometer scale accuracy under realistic conditions; tracking accuracy decreases with increasing noise. Surprisingly, accuracy is found to be insensitive to the numerical aperture, but, as expected, it scales with magnification, with higher magnification yielding improved accuracy (within limits of signal-to-noise). When noise is present at reasonable levels, the effect of image compression is in most cases small. Finally, we provide a free, robust implementation of a tracking algorithm that is easily downloaded and installed.

The inner mitochondrial membrane has been shown to have a novel structure that contains tubular components whose radii are of the order of 10 nm as well as comparatively flat regions. The structural organization of mitochondria is important for understanding their functionality. We present a model that can account, thermodynamically, for the observed size of the tubules. The model contains two lipid constituents with different shapes. They are allowed to distribute in such a way that the composition differs on the two sides of the tubular membrane. Our calculations make two predictions: (1) there is a pressure difference of 0.2 atmospheres across the inner membrane as a necessary consequence of the experimentally observed tubule radius of 10 nm, and (2) migration of differently shaped lipids causes concentration variations of the order of 7% between the two sides of the tubular membrane.